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A method for estimating urban intersection flow based on float vehicle data

A technology of floating car data and intersections, which is used in traffic flow detection, neural learning methods, data processing applications, etc.

Active Publication Date: 2019-01-29
NORTH CHINA UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

Therefore, there are inherent deficiencies and shortcomings in the traditional traffic flow acquisition method

Method used

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  • A method for estimating urban intersection flow based on float vehicle data
  • A method for estimating urban intersection flow based on float vehicle data
  • A method for estimating urban intersection flow based on float vehicle data

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specific Embodiment approach

[0064]Floating car data collection: Use the on-board device or taxi-hailing software installed on taxis and online car-hailing software to collect real-time motion status information of floating cars, including vehicle id, vehicle latitude and longitude, vehicle point speed, vehicle running time stamp, etc., among which The data is transmitted to the central server through the wireless network. The sampling and transmission frequency of the data is high frequency and medium frequency (sampling and transmission interval<5s / time is called high frequency, 5s / time<sampling and transmission interval<15s / time is called High frequency), the floating car data type includes vehicle ID, time, status (heavy vehicle | task vehicle | empty vehicle |), longitude and latitude / head direction / vehicle speed, associated road section number, intersection number, parallel road information, etc.

[0065] Map road network information extraction: through the API interfaces provided by map manufacturer...

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Abstract

A method for estimating urban intersection flow based on float vehicle data is provided. Firstly, the relationship between phase flow and vehicle delay is quantitatively described by Webster delay theorem, and the phase flow is calculated by measuring the delay of floating vehicles passing through the intersection as input data. Secondly, considering the low accuracy of the calculated traffic data, the RBF neural network approximation algorithm is used to modify the data. The comprehensive performance index of the approximation parameters is obtained by measuring the delay and travel time of the floating vehicle as a sub-term. By using the method, the phase flow data with high accuracy can be obtained by using the floating vehicle data, which can provide support for the signal control andoptimization of the urban intersection, thereby effectively improving the control efficiency of the urban intersection, and achieving the purpose of alleviating congestion.

Description

technical field [0001] The invention belongs to the technical field of urban intelligent transportation, and in particular relates to an urban intersection flow estimation technology utilizing low-ratio floating data, which provides data support for intersection signal control and optimization. Background technique [0002] Obtaining the flow data of each phase of the urban intersection is the premise of traffic signal control. There are two traditional methods of obtaining flow data: one is measured by a fixed detector deployed behind the stop line at the controlled intersection. The representative ones are the SCOOT traffic control system in the UK and the SCATS traffic control system in Australia; the other is obtained through manual or manual hand-held device measurement. This method is often used. Urban traffic flow driven by travel demand has temporal and spatial characteristics, most notably including macroscopic regularity, microscopic volatility, randomness, nonlin...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/26G06N3/08G08G1/01G08G1/065
CPCG06N3/08G06Q10/04G06Q50/26G08G1/0104G08G1/065
Inventor 张立立王力张海波何忠贺
Owner NORTH CHINA UNIVERSITY OF TECHNOLOGY
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